BTC Futures_PricesSince BTC prices are diverging, this set of 4 indicators charts volume-weighted prices for different exchanges:
Spot, Tether, Futures and South Korea.
I tried doing EUR & JPY, but the divergence is minimal so its a little pointless.
Here is the 4 links:
חפש סקריפטים עבור "btc股市下跌"
BTC Spot_PricesSince BTC prices are diverging, this set of 4 indicators charts volume-weighted prices for different exchanges:
Spot, Tether, Futures and South Korea.
I tried doing EUR & JPY, but the divergence is minimal so its a little pointless.
Here is the 4 links:
BTC Tether_PricesSince BTC prices are diverging, this set of 4 indicators charts volume-weighted prices for different exchanges:
Spot, Tether, Futures and South Korea.
I tried doing EUR & JPY, but the divergence is minimal so its a little pointless.
Here is the 4 links:
BTC-USD: LONGS, SHORTS & RATIO (Bitfinex)This script allows you
1. to plot the outstanding BTC long (green) and/or short (red) positions
2. to plot an area (blue) corresponding to the ratio between the outstanding long and short positions, shifted and rescaled, such that the zero-line corresponds to the mid-point between the long and short positions: ratio => ratio * mid + mid
BTC Margin Sniper w/ AlertsMargin Sniper uses 2 levels for overbought and oversold to overlay possible trades on the chart. You can adjust its sensitivity by either increasing or decreasing the overbought and oversold threshold numbers. It must meet one of these levels and the short-term trend has to change direction for it to create the alert and entry on the overlay.
Increasing the overbought input makes the trigger more precise, but it may not trigger as often. Decreasing the oversold input will do the same for that trigger.
You can adjust the alerts and the overlaid position suggestions to match your preferred leverage amount.
To set an alert, click "add alert", then select this script. Choose one of the oversold or overbought alerts and enter your message.
I primarily use this on BitMEX with BTC, but you can use it with other exchanges and coins. You may have to adjust the inputs depending on the coin and the timeframe you use. Do not blindly follow this to make purchases. This is just an alert system to notify you of possible trades.
BTC CorrelationA simple script to display how correlated the current ticker is to Bitcoin.
Inputs are the number of bars to check correlation for (default 10) and the the ticker to use for BTC comparison (default is BITFINEX:BTCUSD)
Values of 1 are highly correlated (i.e. bitcoin moves up, so does your current ticker), values of -1 are inversely correlated (i.e. bitcoin moves up, your current ticker moves down).
See: www.babypips.com for some more details on correlation
BTC Volume in FiatThis indicator shows volume in Fiat. You will get wierd numbers if you use it on non BTC-FIAT pairs.
Bitcoin Power Law Bands (BTC Power Law) Indicator█ OVERVIEW
The 'Bitcoin Power Law Bands' indicator is a set of three US dollar price trendlines and two price bands for bitcoin , indicating overall long-term trend, support and resistance levels as well as oversold and overbought conditions. The magnitude and growth of the middle (Center) line is determined by double logarithmic (log-log) regression on the entire USD price history of bitcoin . The upper (Resistance) and lower (Support) lines follow the same trajectory but multiplied by respective (fixed) factors. These two lines indicate levels where the price of bitcoin is expected to meet strong long-term resistance or receive strong long-term support. The two bands between the three lines are price levels where bitcoin may be considered overbought or oversold.
All parameters and visuals may be customized by the user as needed.
█ CONCEPTS
Long-term models
Long-term price models have many challenges, the most significant of which is getting the growth curve right overall. No one can predict how a certain market, asset class, or financial instrument will unfold over several decades. In the case of bitcoin , price history is very limited and extremely volatile, and this further complicates the situation. Fortunately for us, a few smart people already had some bright ideas that seem to have stood the test of time.
Power law
The so-called power law is the only long-term bitcoin price model that has a chance of survival for the years ahead. The idea behind the power law is very simple: over time, the rapid (exponential) initial growth cannot possibly be sustained (see The seduction of the exponential curve for a fun take on this). Year-on-year returns, therefore, must decrease over time, which leads us to the concept of diminishing returns and the power law. In this context, the power law translates to linear growth on a chart with both its axes scaled logarithmically. This is called the log-log chart (as opposed to the semilog chart you see above, on which only one of the axes - price - is logarithmic).
Log-log regression
When both price and time are scaled logarithmically, the power law leads to a linear relationship between them. This in turn allows us to apply linear regression techniques, which will find the best-fitting straight line to the data points in question. The result of performing this log-log regression (i.e. linear regression on a log-log scaled dataset) is two parameters: slope (m) and intercept (b). These parameters fully describe the relationship between price and time as follows: log(P) = m * log(T) + b, where P is price and T is time. Price is measured in US dollars , and Time is counted as the number of days elapsed since bitcoin 's genesis block.
DPC model
The final piece of our puzzle is the Dynamic Power Cycle (DPC) price model of bitcoin . DPC is a long-term cyclic model that uses the power law as its foundation, to which a periodic component stemming from the block subsidy halving cycle is applied dynamically. The regression parameters of this model are re-calculated daily to ensure longevity. For the 'Bitcoin Power Law Bands' indicator, the slope and intercept parameters were calculated on publication date (March 6, 2022). The slope of the Resistance Line is the same as that of the Center Line; its intercept was determined by fitting the line onto the Nov 2021 cycle peak. The slope of the Support Line is the same as that of the Center Line; its intercept was determined by fitting the line onto the Dec 2018 trough of the previous cycle. Please see the Limitations section below on the implications of a static model.
█ FEATURES
Inputs
• Parameters
• Center Intercept (b) and Slope (m): These log-log regression parameters control the behavior of the grey line in the middle
• Resistance Intercept (b) and Slope (m): These log-log regression parameters control the behavior of the red line at the top
• Support Intercept (b) and Slope (m): These log-log regression parameters control the behavior of the green line at the bottom
• Controls
• Plot Line Fill: N/A
• Plot Opportunity Label: Controls the display of current price level relative to the Center, Resistance and Support Lines
Style
• Visuals
• Center: Control, color, opacity, thickness, price line control and line style of the Center Line
• Resistance: Control, color, opacity, thickness, price line control and line style of the Resistance Line
• Support: Control, color, opacity, thickness, price line control and line style of the Support Line
• Plots Background: Control, color and opacity of the Upper Band
• Plots Background: Control, color and opacity of the Lower Band
• Labels: N/A
• Output
• Labels on price scale: Controls the display of current Center, Resistance and Support Line values on the price scale
• Values in status line: Controls the display of current Center, Resistance and Support Line values in the indicator's status line
█ HOW TO USE
The indicator includes three price lines:
• The grey Center Line in the middle shows the overall long-term bitcoin USD price trend
• The red Resistance Line at the top is an indication of where the bitcoin USD price is expected to meet strong long-term resistance
• The green Support Line at the bottom is an indication of where the bitcoin USD price is expected to receive strong long-term support
These lines envelope two price bands:
• The red Upper Band between the Center and Resistance Lines is an area where bitcoin is considered overbought (i.e. too expensive)
• The green Lower Band between the Support and Center Lines is an area where bitcoin is considered oversold (i.e. too cheap)
The power law model assumes that the price of bitcoin will fluctuate around the Center Line, by meeting resistance at the Resistance Line and finding support at the Support Line. When the current price is well below the Center Line (i.e. well into the green Lower Band), bitcoin is considered too cheap (oversold). When the current price is well above the Center Line (i.e. well into the red Upper Band), bitcoin is considered too expensive (overbought). This idea alone is not sufficient for profitable trading, but, when combined with other factors, it could guide the user's decision-making process in the right direction.
█ LIMITATIONS
The indicator is based on a static model, and for this reason it will gradually lose its usefulness. The Center Line is the most durable of the three lines since the long-term growth trend of bitcoin seems to deviate little from the power law. However, how far price extends above and below this line will change with every halving cycle (as can be seen for past cycles). Periodic updates will be needed to keep the indicator relevant. The user is invited to adjust the slope and intercept parameters manually between two updates of the indicator.
█ RAMBLINGS
The 'Bitcoin Power Law Bands' indicator is a useful tool for users wishing to place bitcoin in a macro context. As described above, the price level relative to the three lines is a rough indication of whether bitcoin is over- or undervalued. Users wishing to gain more insight into bitcoin price trends may follow the author's periodic updates of the DPC model (contact information below).
█ NOTES
The author regularly posts on Twitter using the @DeFi_initiate handle.
█ THANKS
Many thanks to the following individuals, who - one way or another - made the 'Bitcoin Power Law Bands' indicator possible:
• TradingView user 'capriole_charles', whose open-source 'Bitcoin Power Law Corridor' script was the basis for this indicator
• Harold Christopher Burger, whose Bitcoin’s natural long-term power-law corridor of growth article (2019) was the basis for the 'Bitcoin Power Law Corridor' script
• Bitcoin Forum user "Trololo", who posted the original power law model at Logarithmic (non-linear) regression - Bitcoin estimated value (2014)
SOL & BTC EMA with BTC/SOL Price Difference % and BTC Dom EMAThis script is designed to provide traders with a comprehensive analysis of Solana (SOL) and Bitcoin (BTC) by incorporating Exponential Moving Averages (EMAs) and price difference percentages. It also includes the BTC Dominance EMA to offer insights into the overall market dominance of Bitcoin.
Features:
SOL EMA: Plots the Exponential Moving Average (EMA) for Solana (SOL) based on a customizable period length.
BTC EMA: Plots the Exponential Moving Average (EMA) for Bitcoin (BTC) based on a customizable period length.
BTC Dominance EMA: Plots the Exponential Moving Average (EMA) for BTC Dominance, which helps in understanding Bitcoin's market share relative to other cryptocurrencies.
BTC/SOL Price Difference %: Calculates and plots the percentage difference between BTC and SOL prices, adjusted for their respective EMAs. This helps in identifying relative strength or weakness between the two assets.
Background Highlight: Colors the background to visually indicate whether the BTC/SOL price difference percentage is positive (green) or negative (red), aiding in quick decision-making.
Inputs:
SOL Ticker: Symbol for Solana (default: BINANCE
).
BTC Ticker: Symbol for Bitcoin (default: BINANCE
).
BTC Dominance Ticker: Symbol for Bitcoin Dominance (default: CRYPTOCAP
.D).
EMA Length: The length of the EMA (default: 20 periods).
Usage:
This script is intended for traders looking to analyze the relationship between SOL and BTC, using EMAs to smooth out price data and highlight trends. The BTC/SOL price difference percentage can help traders identify potential trading opportunities based on the relative movements of SOL and BTC.
Note: Leverage trading involves significant risk and may not be suitable for all investors. Ensure you have a good understanding of the market conditions and employ proper risk management techniques.
Correlation prix [SP500, TESLA, BTCBefore you see this post I want to thank all the TradingView team. Every day that passes I learn better and better to use Pine script and I owe this to all those who publish and to the philosophy of TradingView. Thanks from Amos
This trading indicator compares the prices of the S&P 500 Index (SP500), Tesla (TSLA), and Bitcoin (BTC) to find correlations between them. To make the prices of SP500 and Tesla comparable to the price of Bitcoin, the indicator multiplies the closing price of Tesla by 114 and the closing price of the S&P 500 Index by 5.6.
In this way we can superimpose the prices on the BTC chart and see what happens.
Average BTC price/ tesla price = 114, so if we multiply the tesla price by 114 times we can superimpose it on the BTC price
At average BTC/SPX price = 5.6, also in this case we multiply the price of SPX by 5.6 to overlay the graph and see any correlations.
The indicator then calculates the average price between SP500 and Tesla, using the formula (SP500 + Tesla) / 2. This calculation creates a new line on the chart that represents the average price between these two assets.
The BTC_SP_TE variable is then calculated as the average of the closing price of Bitcoin and the previously calculated average price of SP500 and Tesla, using the formula (Btc + SP_TE) / 2. This calculation creates another line on the chart that represents the average price between Bitcoin and the previously calculated average between SP500 and Tesla.
The idea behind calculating these averages is to find correlations and patterns between the prices of these assets, which can help identify potential trading opportunities. By comparing the average prices of different assets, the trader can look for trends and patterns that might not be apparent when looking at each asset individually.
The indicator plots these prices on a chart and fills the area between them with either green or fuchsia, depending on which one is higher. The strategy suggests buying Bitcoin when the average price of SP500 and Tesla is higher than the current price of Bitcoin, and selling when it is lower.
To add visual cues to the trading strategy, the indicator uses the plotchar function to display a small triangle below the chart when it detects a potential buying opportunity. This is done with the following parameters:
Value: BTC_SP_TE < Btc and Btc > Btc1 and Btc1 > Btc , which is a logical expression that checks whether the average price of SP500 and Tesla is less than the current price of Bitcoin (BTC_SP_TE < Btc), and whether the current price of Bitcoin is higher than the price 10 bars ago (Btc > Btc1 ) and higher than the price on the previous bar (Btc1 > Btc ).
Text: "Moyen BTC_SP_Te", which is the text to display inside the marker.
Symbol: "▲", which is the symbol to use for the marker. In this case, it is a small triangle pointing upwards.
Location: location.belowbar, which specifies that the marker should be placed below the bar.
I hope this is an example of how to create an indicator on TradingView, remember that correlations do not always last, it is possible that when you see the graph this correspondence no longer exists, do your studies and get inspired.
BTC-OTHERS Liquidity PivotBTC-OTHERS Liquidity Map – 1-hour Multi-Asset Pivot Scanner
WHAT IT DOES
This script tracks liquidity shifts between Bitcoin (BTC) and the broader alt-coin market (the OTHERS market-cap index that excludes the top-10 coins). It labels every confirmed 1-hour swing high or low on both assets, then flags four states:
BearPivot – BTC prints a new swing High while OTHERS does not; liquidity crowds into BTC and alts are weak.
BullPivot – BTC prints a swing Low and OTHERS forms a Higher Low; fresh liquidity starts flowing into stronger alts.
BearCon – BTC prints a swing Low and OTHERS forms a Lower Low; down-trend continuation.
BullCon – No new BTC Low while OTHERS makes a Higher High; up-trend continuation.
Signals appear on the actual pivot bar (offset back by the look-back length), so they never repaint after confirmation.
HOW THE PIVOTS ARE FOUND
• Symmetrical window: “Pivot Len” bars to the left and right (default 21).
• Full confirmation on both sides delivers stable, non-repainting pivots at the cost of about Pivot Len bars’ delay.
• Labels are offset –Pivot Len so they sit on the genuine extreme.
INPUTS
Symbols: BTC symbol and an OTHERS symbol so you can switch exchanges or choose another alt index.
Pivot Len: tighten for faster but noisier signals; widen for cleaner pivots.
Style: customise shape and text colours.
PLOTS AND ALERTS
Four labelled shapes (BearPivot, BullPivot, BearCon, BullCon) plot above or below price. Each label is linked to an alertcondition, so you can create one-click alerts and stay informed without watching the screen.
TYPICAL WORKFLOW
1. Attach the script to any 1-hour BTC chart (or leave the script’s timeframe empty to follow your current chart TF).
2. Turn on alerts to receive push/email notifications.
3. Use the labels as a liquidity compass, combining them with volume, funding or your own strategy for actual entries and exits.
Enjoy and trade safe.
BTC Mining Income Oscillator Z-ScoreBTC Mining Income Oscillator (Z-Score)
Overview
The BTC Mining Income Oscillator (Z-Score) is a custom technical indicator that analyzes Bitcoin mining income to help traders identify overbought and oversold conditions. The indicator uses a Z-Score to track deviations in mining income, highlighting periods of high or low mining profitability.
This indicator is made up of:
Z-Score Line (Blue): Measures how far the current mining income deviates from its historical mean.
Mining Income Oscillator (Orange): A scaled value of mining income that oscillates within a specific range to indicate overbought and oversold conditions.
How the Indicator Works
1. Mining Income Calculation
The BTC Mining Income is determined using two main factors:
Block Reward: The number of BTC miners earn for each block mined (currently 3.125 BTC, adjustable in settings).
Transaction Fees: The average transaction fees per block (default is 0.3 BTC).
Blocks per Day: The number of blocks mined per day (default is 144).
The daily mining income in BTC is calculated as:
Mining Income
=
(
Block Reward
+
Transaction Fees
)
×
Blocks per Day
Mining Income=(Block Reward+Transaction Fees)×Blocks per Day
This value is then converted to USD by multiplying it by the current Bitcoin price.
2. Z-Score Calculation
The Z-Score measures how far the current mining income deviates from its mean over a set period (default is 90 days). The Z-Score helps identify when mining income is unusually high or low:
A high Z-Score indicates that the mining income is significantly above the historical mean, signaling overbought conditions.
A low Z-Score indicates that the mining income is significantly below the historical mean, signaling oversold conditions.
The Z-Score is calculated as follows:
Z-Score
=
(
Current Mining Income
−
Mean Income
)
Standard Deviation
Z-Score=
Standard Deviation
(Current Mining Income−Mean Income)
The result is then smoothed over a period (default is 5) to reduce noise and provide a more stable value.
3. Mining Income Oscillator
The mining income is scaled to oscillate between +20 and +90. This oscillation makes it easy to track overbought and oversold conditions in the market:
Values between 85 and 90 indicate overbought conditions (high mining profitability).
Values between 20 and 22 indicate oversold conditions (low mining profitability).
Values between 22 and 85 indicate neutral conditions, where mining profitability is normal.
The mining income oscillator helps traders spot extreme conditions (overbought or oversold) in mining profitability.
How to Read the Indicator
1. Z-Score Line (Blue)
The Z-Score represents how far current mining income is from the historical average.
Above +2: The mining income is unusually high, indicating an overbought market.
Below -2: The mining income is unusually low, indicating an oversold market.
Between -2 and +2: This range is neutral, where the mining income is within the average historical range.
2. Mining Income Oscillator (Orange)
The Mining Income Oscillator is scaled between 20 and 90.
85–90: Overbought conditions, indicating high mining profitability.
20–22: Oversold conditions, indicating low mining profitability.
22–85: Neutral conditions, indicating moderate mining profitability.
3. Background Shading
Red Shading (85–90): Indicates overbought conditions (mining income is unusually high).
Green Shading (20–22): Indicates oversold conditions (mining income is unusually low).
The shaded regions provide a visual guide to spot periods when the market is overbought or oversold.
4. Key Horizontal Lines
0 Line: Represents the neutral level for the Z-Score, where the mining income is at the historical mean.
+2 and -2 Lines: Indicate overbought and oversold conditions for the Z-Score.
90 and 20 Lines: Indicate the upper and lower bounds for the mining income oscillator.
Where the Data Comes From
Bitcoin Price: The current Bitcoin price is pulled directly from the chart.
Block Reward and Transaction Fees: These values are set manually by the user or can be updated dynamically.
Mining Income: Calculated based on the block reward, transaction fees, and current Bitcoin price.
Z-Score and Oscillator Calculations: Both are calculated based on mining income in USD over a defined look-back period.
Best Timeframe for This Indicator
This indicator is designed to work best on the 2-day chart (2D) timeframe. On the 2-day chart, the mining income data, Z-Score, and the oscillator are less sensitive to noise and short-term volatility, providing more reliable signals. While it can be used on other timeframes, the 2-day chart offers the clearest and most stable analysis.
Bitcoin Golden Bottom Oscillator (MZ BTC Oscillator)This indicator uses Elliot Wave Oscillator Methodology applied on "BTC Golden Bottom with Adaptive Moving Average" and Relative Strength Index of Resulted EVO to form an Oscillator to detect trend health in Bitcoin price. Ticker is set to "INDEX : BTCUSD" on 1D timeframe.
Methodology
Oscillator uses Adaptive Moving Average with 1 year of length, Minor length of 50 and Major length of 100 to mark AMA as Golden Bottom.
Percentage Elliot Wave Oscillator is calculated between BTC price and AMA.
Relative Strength Index of EVO is calculated to detect trend strength and divergence detection.
Hull Moving Average of resulted RSI is used to smoothen the Oscillator.
Oscillator is hard coded to 'INDEX:BTCUSD' ticker on 1d so it can be used on any other chart and on any other timeframe.
Color Schemes
Bright Red background color indicates that price has left top Fib multiple ATR band and possibly go for top.
Light Red background color indicates that price has left 2nd top Fib multiple ATR band and possibly go for local top.
Lime background color indicates that price has entered lowest band indicating local bottom.
Bright Green background color indicates that price is approximately resting on Golden Bottom i.e. AMA.
Oscillator color is set to gradient for easy directional adaption.
BTC Golden Bottom with Adaptive Moving Average
[c3s] CWS - M2 Global Liquidity Index & BTC Correlation CWS - M2 Global Liquidity Index with Offset BTC Correlation
This custom indicator visualizes and analyzes the relationship between the global M2 money supply and Bitcoin (BTC) price movements. It calculates the correlation between these two variables to provide insights into how changes in global liquidity may impact Bitcoin’s price over time.
Key Features:
Global M2 Liquidity Index Calculation:
Fetches M2 money supply data from multiple economies (China, US, EU, Japan, UK) and normalizes using currency exchange rates (e.g., CNY/USD, EUR/USD).
Combines all M2 data points and normalizes by dividing by 1 trillion (1e12) for easier visualization.
Offset for M2 Data:
The offset parameter allows users to shift the M2 data by a specified number of days, helping track the influence of past global liquidity on Bitcoin.
BTC Price Correlation:
Computes the correlation between shifted global M2 liquidity and Bitcoin (BTC) price, using a 52-day lookback period by default.
Correlation Quality Display:
Categorizes correlation quality as:
Excellent : Correlation >= 0.8
Good : Correlation >= 0.6 and < 0.8
Weak : Correlation >= 0.4 and < 0.6
Very Weak : Correlation < 0.4
Displays correlation quality as a label on the chart for easy assessment.
Visual Enhancements:
Labels : Displays dynamic labels on the chart with metrics like M2 value and correlation.
Plot Shapes : Uses shapes to indicate data availability for global M2 and correlation.
Data Table : Optionally shows a data table in the top-right corner summarizing:
Global M2 value (in trillions)
The correlation between global M2 and BTC
The correlation quality
Optional Debugging:
Debug plots help identify when data is missing for M2 or correlation, ensuring transparency and accurate functionality.
Inputs:
Offset: Shift the M2 data (in days) to see past liquidity effects on Bitcoin.
Lookback Period: Number of periods (default 52) used to calculate the correlation.
Show Labels: Toggle to show or hide labels for M2 and correlation values.
Show Table: Toggle to show or hide the data table in the top-right corner.
Usage:
Ideal for traders and analysts seeking to understand the relationship between global liquidity and Bitcoin price. The offset and lookback period can be adjusted to explore different timeframes and correlation strengths, aiding more informed trading decisions.
[BCT] Can BTC be predicted or is it purely random?Variance Ratio**This indicator can be applied to the ticker of your choice (not just BTC)**
Markets are said to be "efficient". An efficient market is by definition unpredictable - no matter the amount of ML, computation, or indicators thrown at it. In particular, in an efficient market, TA will not be of help.
An illustration of efficient markets is the WSJ's longstanding monkey vs. human contest:Blindfolded Monkey Beats Humans With Stock Picks, granted there are several flaws to it.
BTC is a relatively new market. New markets are typically highly inefficient (easier to make money) and become more and more efficient over time (harder to make money). How much more efficient is BTC becoming?
We apply the Variance Ratio method and apply it to BTC.
BACKGROUND ON THE VARIANCE RATIO METHOD
Based on 1988 MacKinlay's seminal paper "Stock Market Prices do not Follow a Random Walk", the idea is to exploit a phenomenon called "variance scaling".
For those keen on looking into the math, the short version of it is under the assumption of iid (random walk) we have the following:
H0: Var(Sum(returns over K bars))=Sum(Var(returns over 1 bar))=k*Var(return over 1 bar)
We look to reject or not H0 depending on the observations.
In this script, we compare the variance of the (log) returns for the chart selected between:
(1) The (average) variance over k bars (call this Vk)
(2) The (average) variance over 1 bar (call this V1)
H0 simply says that Vk=k*V1 if the stock follows a random walk.
We compute the Variance Ratio VR(k)=Variance(returns over k bar)/(Sum(Var(returns over 1 bar)))-1
We then compute the associated Z-score which we chart out for a configurable k number of bars.
HOW TO INTERPRET THE CHART
The line drawn is the Z-Score for VR(k). It represents the number of standard deviations of VR(k) from 0 - the further out, the less random.
- If the line is close / hovers around 0, the ticker appears to follow a random walk (i.e. may not be predictable)
- If the line is consistently > 2 or <-2, the ticker likely does not follow a random walk (i.e. may have predictable features)
- If the line is positive, it means that the Variance on the k bars is larger than the variance on 1 bar (more variance on longer timeframes)
- If the line is negative, it means that the Variance on the k bars is smaller than the variance on 1 bar (more variance on smaller timeframes)
USE CASES
- Identify timeframes where you won't be able to make money
- Identify whether a stock cannot be predicted (forget about TA, indicators etc. -- a random walk is not predictable)
- Identify whether a stock is becoming less and less predictable (Z-score amplitude will decrease over time)
FEATURES
- select the number of K bar to compare vs. 1 bar (default = 16) - ideally a power of 2 but any other number will work. The chart is based off this selection
- select the lookback period for the analysis (500 bars by default)
- select the source to analyze (default = close, but you may select other inputs to calculate the returns from)
- results form the statistical tests on different K's in the table on the right/bottom side of the chart (H0 rejected = not random walk; H0 not rejected = it essentially looks rather random and we can't conclude that it's not a random walk)
COMMENTARY ON BTC
- It appears BTC's absolute value of the ZScore on the Variance Ratio is declining year after year - corroborating an increasingly efficient market as new participants join.
- However, we can still detect a fair amount of potential inefficiency using this simple test.
As usual, this is not investment advice. DYOR.
With love,
🐵BCT🐵
BTC Trend Momentum (BTM) with VWMOBTC Trend Momentum (BTM) with VWMO – A Smarter Way to Trade Bitcoin 🚀
Overview
Bitcoin price movements can be volatile, often leading to fake breakouts and whipsaws that mislead traders. BTC Trend Momentum (BTM), combined with Volume Weighted Moving Average (VWMO), helps smooth out market noise and provide clearer trend signals.
This script integrates momentum analysis, trend strength detection, and zero-line crossovers, allowing traders to make smarter entries and exits while avoiding false signals.
⸻
Why Use This Indicator?
✅ Momentum Histogram – Easily visualize trend strength with color-coded bars.
✅ Volume-Weighted Analysis – Uses VWMO to filter out weak price movements.
✅ Zero Line Crossover Alerts – Identifies major trend shifts in real-time.
✅ Dynamic Color Coding – Stronger trends highlighted in brighter colors.
✅ Background Shading – Differentiates bullish & bearish zones for easy trend reading.
✅ Built-in Alerts – Get notified of trade opportunities instantly.
⸻
How to Trade Using BTC Trend Momentum (BTM)
🔹 Buy Signal: When the momentum histogram (green bars) crosses above the EMA (orange line).
🔹 Sell Signal: When the momentum histogram (red bars) crosses below the EMA.
🔹 Strong Trend Confirmation: If histogram bars turn lime (bullish) or maroon (bearish), it indicates strong momentum.
🔹 Zero Line Crossovers: A bullish crossover above zero confirms an uptrend, while a bearish crossover below zero confirms a downtrend.
For better results, combine with RSI, MACD, or VWAP to confirm trend strength before entering trades.
⸻
Best Timeframes for Trading
📌 1H & 4H – Ideal for swing trading Bitcoin.
📌 5M & 15M – Perfect for scalping BTC with precision.
⸻
💡 Would you integrate BTC Trend Momentum (BTM) into your trading strategy? Let us know your thoughts below!
TOTAL3/BTC This Pine Script™ code, named "TOTAL3/BTC with Arrow," is designed for cryptocurrency analysis on TradingView.
This script essentially provides a visual tool for traders to gauge when altcoins might be gaining or losing ground relative to Bitcoin through moving average analysis and color-coded trend indication.
Intention was to help the community with a script based on classic TA only.
Use it with SASDv2r indicator.
Feel free to make it better. If you did so, please let me know.
Main elements:
Data Fetching: It retrieves market cap data for all cryptocurrencies excluding Bitcoin and Ethereum (TOTAL3) and for Bitcoin (BTC).
Ratio Calculation: The script calculates the ratio of TOTAL3 to BTC market caps, which indicates how altcoins (excluding ETH) are performing relative to Bitcoin.
Plotting the Ratio: This ratio is plotted on the chart with a blue line, allowing traders to see the relative performance visually.
Moving Averages: Two Simple Moving Averages (SMA) are calculated for this ratio, one for 20 periods (ma20) and another for 50 periods (ma50), though these are not plotted in the current version of the code.
Reference Lines: Horizontal lines are added at ratios of 0.3 and 0.8 to serve as visual equilibrium points or thresholds for analysis.
Complex Moving Average: The script uses constants (len, len2, cc, smoothe) from another script, suggesting it's adapting or simplifying another's logic for multi-timeframe analysis.
Average Calculation: Two SMAs (avg and avg2) are computed using the constants defined, focusing on different lengths for trend analysis.
Direction Determination: It checks if the moving average is trending up or down by comparing the current value with its value smoothe bars earlier.
Color Coding: The color of the plotted moving average changes based on its direction (lime for up, red for down, aqua if no clear direction), aiding in quick visual interpretation of trends.
Plotting: Finally, the script plots this multi-timeframe moving average with a dynamic color to reflect the current market trend of the TOTAL3/BTC ratio, with a thicker line for visibility.
BTC Slayer 9000 - Relative Risk-adjusted performanceBTC Slayer 9000: Relative Risk-Adjusted Performance
Dear friends and fellow traders,
I am pleased to introduce the BTC Slayer 9000, a script designed to provide clear insights into risk-adjusted performance relative to a benchmark. Whether you're navigating the volatile world of cryptocurrencies or exploring opportunities in stocks, this tool helps you make informed decisions by comparing assets against your chosen benchmark.
What Does It Do?
This indicator is based on the Ulcer Index (UI), a metric that measures downside risk. It calculates the Ulcer Performance Index (UPI), which combines returns and downside risk, and compares it to a benchmark (like BTC/USDT, SPY500, or any trading pair).
The result is the Relative UPI (RUPI):
Positive RUPI (green area): The asset's risk-adjusted performance is better than the benchmark.
Negative RUPI (red area): The asset's risk-adjusted performance is worse than the benchmark.
Why Use It?
Risk vs. Reward: See if the extra risk of an asset is justified by its returns.
Customizable Benchmark: Compare any asset against BTC, SPY500, or another chart.
Dynamic Insights: Quickly identify outperforming assets for long positions and underperformers for potential shorts.
How to Use:
Inputs:
Adjust the lookback period to set the time frame for analysis. 720 Period is meant to represent 30 days. I like to use 168 period because I do not hold trades for long.
Choose your comparison chart (e.g., BTC/USDT, SPY500, AAPL, etc.).
Interpretation:
Green Area Above 0: The asset offers better risk-adjusted returns than the benchmark.
Red Area Below 0: The benchmark is a safer or more rewarding option.
Perfect for All Traders
Whether you:
Trade Cryptocurrencies: Compare altcoins to BTC.
Invest in Stocks: Compare individual stocks to indices like SPY500.
Evaluate Portfolio Options: Decide between assets like AAPL or TSLA.
This indicator equips you with a systematic way to evaluate "Is the extra risk worth it?".
The script was compiled in Collaboration with ChatGPT
Anchored BTCIntroduce
When looking at altcoins and bitcoins together and seeing coupling and decoupling, we add a bitcoin chart in the "Compare" tab.
We checked where the coupling occurs in "Auto" mode, but if we move the chart, the overlapped position will change.
So I created the “Anchored BTC” indicator, which made the Bitcoin chart immovable.
How to use
First, add a bitcoin chart in the "Compare" tab and compare it with the altcoin chart.
And add the "Correlation Coefficient" built-in indicator to find the part where the correlation coefficient is 0.8 or higher.(it means finding well coupled part)
Among them, set the swing high or swing low part to Time1 and Time2.
Check if it looks the same as the existing BTC chart and you are done.
소개
알트코인과 비트코인을 함께 보며 커플링과 디커플링을 볼 때 우리는 비교 탭에서 비트코인 차트를 추가하여 봅니다.
"오토" 모드로 어느 부분에서 커플링이 일어나는지 체크했는데 차트를 옮기면 겹쳐놓아졌던 위치가 달라지게됩니다.
그래서 "Anchored BTC" 지표를 만들어, 비트코인 차트가 움직이지 못하게 만들었습니다.
사용법
우선 비교탭에서 비트코인차트를 추가하여 알트코인 차트와 비교해봅니다.
그리고 "상관계수" 빌트인 지표를 추가하여 상관계수가 0.8이상인 부분을 찾습니다.(커플링한 부분을 찾는겁니다)
이 중에서 스윙하이나 스윙로우인 부분을 Time1, Time2로 맞춰줍니다.
기존의 BTC차트와 동일하게 보여지는지 확인하면 끝납니다.
FTX vs BitMex BTC Perp PremiumThis script compares FTX BTC/PERP (BTC perpetual futures contract) price to Binance BTC/USDT spot and colors it red. It also plots Bitmex's BTC perpetual futures compared to Binance spot and colors it blue.
FTX = red
Bitmex = blue
Now you can easily see that you can get a 1% discount on FTX perpetuals when it is tanking. This tells you that you can set your limit buy orders extra low if you like to catch crashes. Also, you can see what your average trader on each platform is willing to pay above or below the spot premium. In general you want to do the opposite of what the average trading is doing on these exchanges unless you're in the main bull or mania phase of the Bitcoin cycle.
If you want to use Bitstamp or your favorite exchange it can be changed in the settings. Let me know if you find any settings that work well for you.
May you profit and enjoy! :)
BTC Spread: Coinbase Spot vs CME Futures (skullcap)BTC Spread: Coinbase Spot vs CME Futures
This indicator plots the real-time spread between Coinbase Spot BTC (COINBASE:BTCUSD) and CME Bitcoin Futures (CME:BTC1!).
It allows traders to monitor the premium or discount between spot and futures markets directly in one chart.
⸻
📊 How it Works
• The script pulls Coinbase spot BTC closing prices and CME front-month BTC futures prices on your selected timeframe.
• The spread is calculated as:
Spread = CME Price – Coinbase Spot Price
🔧 How to Use
1. Add the indicator to your chart (set to any timeframe you prefer).
2. The orange line represents the spread (USD difference).
3. The grey dashed line marks the zero level (parity between CME and Coinbase).
4. Use it to:
• Compare futures vs. spot market structure
• Track premium/discount cycles around funding or expiry
• Identify arbitrage opportunities or market dislocations
⸻
⚠️ Notes
• This indicator is informational only and does not provide trading signals.
• Useful for traders analysing derivatives vs spot price action.
• Works best when paired with order flow, funding rate, and open interest data.
BTC & SPX vs Yield Curve: Recession Risk ZonesBTC & SPX vs Yield Curve – Recession Risk Zones
This tool helps you track Bitcoin (BTC) and the S&P 500 (SPX) against key macro signals from the U.S. yield curve to spot potential recession risks.
🟪 Color Legend:
🔴 Red = Yield curve is inverted (warning starts)
🟡 Yellow = Projected 6–18 month recession risk (if inversion still active)
🟠 Orange = Active 6–18 month risk window (after inversion ends)
💜 Fuchsia = Real historical U.S. recessions
📈 What’s Plotted:
🔵 BTCUSD (blue line) – Normalized price
🟢 S&P 500 (green line) – Normalized price
🟠 10Y–2Y Yield Spread – Macro signal for risk
✅ Use it to:
Spot macro pressure zones
See how BTC and SPX behave around economic stress
Stay cautious when red/orange/yellow areas appear
Let me know if you'd like to enable toggles to hide/show BTC or SPX independently!
TSI Long/Short for BTC 2HThe TSI Long/Short for BTC 2H strategy is an advanced trend-following system designed specifically for trading Bitcoin (BTC) on a 2-hour timeframe. It leverages the True Strength Index (TSI) to identify momentum shifts and executes both long and short trades in response to dynamic market conditions.
Unlike traditional moving average-based strategies, this script uses a double-smoothed momentum calculation, enhancing signal accuracy and reducing noise. It incorporates automated position sizing, customizable leverage, and real-time performance tracking, ensuring a structured and adaptable trading approach.
🔹 What Makes This Strategy Unique?
Unlike simple crossover strategies or generic trend-following approaches, this system utilizes a customized True Strength Index (TSI) methodology that dynamically adjusts to market conditions.
🔸 True Strength Index (TSI) Filtering – The script refines the TSI by applying double exponential smoothing, filtering out weak signals and capturing high-confidence momentum shifts.
🔸 Adaptive Entry & Exit Logic – Instead of fixed thresholds, it compares the TSI value against a dynamically determined high/low range from the past 100 bars to confirm trade signals.
🔸 Leverage & Risk Optimization – Position sizing is dynamically adjusted based on account equity and leverage settings, ensuring controlled risk exposure.
🔸 Performance Monitoring System – A built-in performance tracking table allows traders to evaluate monthly and yearly results directly on the chart.
📊 Core Strategy Components
1️⃣ Momentum-Based Trade Execution
The strategy generates long and short trade signals based on the following conditions:
✅ Long Entry Condition – A buy signal is triggered when the TSI crosses above its 100-bar highest value (previously set), confirming bullish momentum.
✅ Short Entry Condition – A sell signal is generated when the TSI crosses below its 100-bar lowest value (previously set), indicating bearish pressure.
Each trade execution is fully automated, reducing emotional decision-making and improving trading discipline.
2️⃣ Position Sizing & Leverage Control
Risk management is a key focus of this strategy:
🔹 Dynamic Position Sizing – The script calculates position size based on:
Account Equity – Ensuring trade sizes adjust dynamically with capital fluctuations.
Leverage Multiplier – Allows traders to customize risk exposure via an adjustable leverage setting.
🔹 No Fixed Stop-Loss – The strategy relies on reversals to exit trades, meaning each position is closed when the opposite signal appears.
This design ensures maximum capital efficiency while adapting to market conditions in real time.
3️⃣ Performance Visualization & Tracking
Understanding historical performance is crucial for refining strategies. The script includes:
📌 Real-Time Trade Markers – Buy and sell signals are visually displayed on the chart for easy reference.
📌 Performance Metrics Table – Tracks monthly and yearly returns in percentage form, helping traders assess profitability over time.
📌 Trade History Visualization – Completed trades are displayed with color-coded boxes (green for long trades, red for short trades), visually representing profit/loss dynamics.
📢 Why Use This Strategy?
✔ Advanced Momentum Detection – Uses a double-smoothed TSI for more accurate trend signals.
✔ Fully Automated Trading – Removes emotional bias and enforces discipline.
✔ Customizable Risk Management – Adjust leverage and position sizing to suit your risk profile.
✔ Comprehensive Performance Tracking – Integrated reporting system provides clear insights into past trades.
This strategy is ideal for Bitcoin traders looking for a structured, high-probability system that adapts to both bullish and bearish trends on the 2-hour timeframe.
📌 How to Use: Simply add the script to your 2H BTC chart, configure your leverage settings, and let the system handle trade execution and tracking! 🚀
